Overview

Dataset statistics

Number of variables30
Number of observations1851
Missing cells13432
Missing cells (%)24.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory434.0 KiB
Average record size in memory240.1 B

Variable types

NUM17
CAT11
UNSUPPORTED1
BOOL1

Warnings

UArt2 has 1584 (85.6%) missing values Missing
AUrs1 has 1660 (89.7%) missing values Missing
AUrs2 has 1840 (99.4%) missing values Missing
AufHi has 1402 (75.7%) missing values Missing
Char1 has 1694 (91.5%) missing values Missing
Char2 has 1809 (97.7%) missing values Missing
Lich2 has 1492 (80.6%) missing values Missing
Zust2 has 1834 (99.1%) missing values Missing
Fstf has 109 (5.9%) missing values Missing
df_index has unique values Unique
WoTag is an unsupported type, check if it needs cleaning or further analysis Unsupported
TempDist has 845 (45.7%) zeros Zeros
SpatDist has 1568 (84.7%) zeros Zeros
UArt1 has 63 (3.4%) zeros Zeros

Reproduction

Analysis started2020-11-13 16:30:22.065538
Analysis finished2020-11-13 16:31:45.379479
Duration1 minute and 23.31 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

df_index
Real number (ℝ≥0)

UNIQUE

Distinct1851
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean933.5440303
Minimum0
Maximum1866
Zeros1
Zeros (%)0.1%
Memory size14.5 KiB
2020-11-13T17:31:45.740738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile92.5
Q1462.5
median936
Q31402.5
95-th percentile1773.5
Maximum1866
Range1866
Interquartile range (IQR)940

Descriptive statistics

Standard deviation540.8130821
Coefficient of variation (CV)0.5793118103
Kurtosis-1.208745946
Mean933.5440303
Median Absolute Deviation (MAD)470
Skewness-0.003498815736
Sum1727990
Variance292478.7898
MonotocityStrictly increasing
2020-11-13T17:31:45.894819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
186510.1%
 
122810.1%
 
123210.1%
 
123410.1%
 
123610.1%
 
123810.1%
 
124010.1%
 
124210.1%
 
124410.1%
 
124610.1%
 
Other values (1841)184199.5%
 
ValueCountFrequency (%) 
010.1%
 
110.1%
 
210.1%
 
310.1%
 
410.1%
 
ValueCountFrequency (%) 
186610.1%
 
186510.1%
 
186410.1%
 
186310.1%
 
186210.1%
 

TempMax
Real number (ℝ≥0)

Distinct208
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean171.7034036
Minimum9
Maximum1341
Zeros0
Zeros (%)0.0%
Memory size14.5 KiB
2020-11-13T17:31:46.209434image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile24
Q169
median117
Q3211.5
95-th percentile498
Maximum1341
Range1332
Interquartile range (IQR)142.5

Descriptive statistics

Standard deviation168.9626605
Coefficient of variation (CV)0.9840379221
Kurtosis10.36837755
Mean171.7034036
Median Absolute Deviation (MAD)63
Skewness2.67088055
Sum317823
Variance28548.38063
MonotocityNot monotonic
2020-11-13T17:31:46.359735image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
84361.9%
 
81361.9%
 
93351.9%
 
87331.8%
 
78311.7%
 
111311.7%
 
72311.7%
 
69311.7%
 
54311.7%
 
96301.6%
 
Other values (198)152682.4%
 
ValueCountFrequency (%) 
980.4%
 
12110.6%
 
15130.7%
 
18281.5%
 
21201.1%
 
ValueCountFrequency (%) 
134110.1%
 
132330.2%
 
125720.1%
 
119410.1%
 
115210.1%
 

TempAvg
Real number (ℝ≥0)

Distinct246
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.11669368
Minimum3
Maximum1326
Zeros0
Zeros (%)0.0%
Memory size14.5 KiB
2020-11-13T17:31:46.509927image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile11
Q132
median55
Q390
95-th percentile196.5
Maximum1326
Range1323
Interquartile range (IQR)58

Descriptive statistics

Standard deviation81.51801258
Coefficient of variation (CV)1.099860349
Kurtosis71.70901825
Mean74.11669368
Median Absolute Deviation (MAD)28
Skewness6.311730476
Sum137190
Variance6645.186375
MonotocityNot monotonic
2020-11-13T17:31:46.653079image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
44301.6%
 
26271.5%
 
48271.5%
 
53261.4%
 
59261.4%
 
24251.4%
 
56241.3%
 
57231.2%
 
33231.2%
 
61231.2%
 
Other values (236)159786.3%
 
ValueCountFrequency (%) 
310.1%
 
430.2%
 
5110.6%
 
6130.7%
 
7181.0%
 
ValueCountFrequency (%) 
132610.1%
 
126010.1%
 
95510.1%
 
92010.1%
 
70310.1%
 

SpatMax
Real number (ℝ≥0)

Distinct1508
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10834.56186
Minimum832
Maximum49765
Zeros0
Zeros (%)0.0%
Memory size14.5 KiB
2020-11-13T17:31:46.795844image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum832
5-th percentile1891
Q14506
median8335
Q314367
95-th percentile29293.5
Maximum49765
Range48933
Interquartile range (IQR)9861

Descriptive statistics

Standard deviation8703.725654
Coefficient of variation (CV)0.8033297302
Kurtosis2.497009375
Mean10834.56186
Median Absolute Deviation (MAD)4536
Skewness1.553324122
Sum20054774
Variance75754840.26
MonotocityNot monotonic
2020-11-13T17:31:46.957182image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1316380.4%
 
662150.3%
 
347550.3%
 
235150.3%
 
150340.2%
 
3549240.2%
 
568640.2%
 
1592740.2%
 
300040.2%
 
1345640.2%
 
Other values (1498)180497.5%
 
ValueCountFrequency (%) 
83220.1%
 
96510.1%
 
97110.1%
 
100010.1%
 
103610.1%
 
ValueCountFrequency (%) 
4976510.1%
 
4827810.1%
 
4632810.1%
 
4607810.1%
 
4513010.1%
 

SpatAvg
Real number (ℝ≥0)

Distinct1490
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3966.494327
Minimum135
Maximum17805
Zeros0
Zeros (%)0.0%
Memory size14.5 KiB
2020-11-13T17:31:47.108335image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum135
5-th percentile1050
Q12002.5
median3387
Q35264
95-th percentile9180
Maximum17805
Range17670
Interquartile range (IQR)3261.5

Descriptive statistics

Standard deviation2598.517013
Coefficient of variation (CV)0.6551167854
Kurtosis2.347916279
Mean3966.494327
Median Absolute Deviation (MAD)1551
Skewness1.350873664
Sum7341981
Variance6752290.667
MonotocityNot monotonic
2020-11-13T17:31:47.256911image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
560650.3%
 
141350.3%
 
882240.2%
 
1236340.2%
 
442340.2%
 
144530.2%
 
390730.2%
 
443130.2%
 
282030.2%
 
334830.2%
 
Other values (1480)181498.0%
 
ValueCountFrequency (%) 
13510.1%
 
34710.1%
 
35810.1%
 
38710.1%
 
39310.1%
 
ValueCountFrequency (%) 
1780510.1%
 
1685110.1%
 
1657120.1%
 
1552610.1%
 
1513210.1%
 

TempDist
Real number (ℝ≥0)

ZEROS

Distinct25
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.566180443
Minimum0
Maximum24
Zeros845
Zeros (%)45.7%
Memory size14.5 KiB
2020-11-13T17:31:47.399727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q39
95-th percentile21
Maximum24
Range24
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.88910785
Coefficient of variation (CV)1.23767239
Kurtosis0.1456204672
Mean5.566180443
Median Absolute Deviation (MAD)3
Skewness1.103172777
Sum10303
Variance47.45980697
MonotocityNot monotonic
2020-11-13T17:31:47.528207image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%) 
084545.7%
 
6884.8%
 
7764.1%
 
5703.8%
 
8673.6%
 
9663.6%
 
10603.2%
 
3583.1%
 
12512.8%
 
4502.7%
 
Other values (15)42022.7%
 
ValueCountFrequency (%) 
084545.7%
 
1412.2%
 
2321.7%
 
3583.1%
 
4502.7%
 
ValueCountFrequency (%) 
24271.5%
 
23211.1%
 
22271.5%
 
21311.7%
 
20191.0%
 

SpatDist
Real number (ℝ≥0)

ZEROS

Distinct220
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.50567261
Minimum0
Maximum2000
Zeros1568
Zeros (%)84.7%
Memory size14.5 KiB
2020-11-13T17:31:47.669505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile650.5
Maximum2000
Range2000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation281.6624937
Coefficient of variation (CV)3.294079622
Kurtosis18.39684028
Mean85.50567261
Median Absolute Deviation (MAD)0
Skewness4.148671881
Sum158271
Variance79333.76037
MonotocityNot monotonic
2020-11-13T17:31:47.824410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0156884.7%
 
250150.8%
 
75080.4%
 
125060.3%
 
5030.2%
 
15130.2%
 
29030.2%
 
17030.2%
 
46820.1%
 
34120.1%
 
Other values (210)23812.9%
 
ValueCountFrequency (%) 
0156884.7%
 
210.1%
 
320.1%
 
710.1%
 
1310.1%
 
ValueCountFrequency (%) 
200020.1%
 
197510.1%
 
196010.1%
 
194910.1%
 
190610.1%
 

Coverage
Real number (ℝ≥0)

Distinct94
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.91356024
Minimum5
Maximum100
Zeros0
Zeros (%)0.0%
Memory size14.5 KiB
2020-11-13T17:31:47.983856image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile14
Q128
median41
Q359
95-th percentile85
Maximum100
Range95
Interquartile range (IQR)31

Descriptive statistics

Standard deviation21.22520391
Coefficient of variation (CV)0.4833405397
Kurtosis-0.365307144
Mean43.91356024
Median Absolute Deviation (MAD)15
Skewness0.5182298826
Sum81284
Variance450.5092809
MonotocityNot monotonic
2020-11-13T17:31:48.137936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
42452.4%
 
30422.3%
 
36422.3%
 
44412.2%
 
25402.2%
 
40402.2%
 
31392.1%
 
37382.1%
 
18361.9%
 
45361.9%
 
Other values (84)145278.4%
 
ValueCountFrequency (%) 
510.1%
 
660.3%
 
760.3%
 
840.2%
 
960.3%
 
ValueCountFrequency (%) 
100181.0%
 
9830.2%
 
9720.1%
 
9640.2%
 
9530.2%
 

TLCar
Real number (ℝ≥0)

Distinct827
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1511.645597
Minimum1000
Maximum1999
Zeros0
Zeros (%)0.0%
Memory size14.5 KiB
2020-11-13T17:31:48.287108image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1051.5
Q11265
median1522
Q31765
95-th percentile1948.5
Maximum1999
Range999
Interquartile range (IQR)500

Descriptive statistics

Standard deviation288.6505935
Coefficient of variation (CV)0.1909512349
Kurtosis-1.206783468
Mean1511.645597
Median Absolute Deviation (MAD)251
Skewness-0.04504740042
Sum2798056
Variance83319.16514
MonotocityNot monotonic
2020-11-13T17:31:48.557597image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
119170.4%
 
190270.4%
 
129370.4%
 
195570.4%
 
185160.3%
 
183660.3%
 
145160.3%
 
142160.3%
 
131560.3%
 
186660.3%
 
Other values (817)178796.5%
 
ValueCountFrequency (%) 
100010.1%
 
100150.3%
 
100220.1%
 
100330.2%
 
100630.2%
 
ValueCountFrequency (%) 
199960.3%
 
199830.2%
 
199720.1%
 
199630.2%
 
199420.1%
 

TLHGV
Real number (ℝ≥0)

Distinct488
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean747.6428957
Minimum500
Maximum999
Zeros0
Zeros (%)0.0%
Memory size14.5 KiB
2020-11-13T17:31:48.704521image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile525
Q1621
median745
Q3871
95-th percentile972
Maximum999
Range499
Interquartile range (IQR)250

Descriptive statistics

Standard deviation144.9141497
Coefficient of variation (CV)0.1938280301
Kurtosis-1.232383906
Mean747.6428957
Median Absolute Deviation (MAD)126
Skewness0.0276876092
Sum1383887
Variance21000.11079
MonotocityNot monotonic
2020-11-13T17:31:48.855355image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
926110.6%
 
869100.5%
 
871100.5%
 
582100.5%
 
79590.5%
 
56790.5%
 
62690.5%
 
66490.5%
 
98290.5%
 
69180.4%
 
Other values (478)175794.9%
 
ValueCountFrequency (%) 
50030.2%
 
50170.4%
 
50230.2%
 
50310.1%
 
50410.1%
 
ValueCountFrequency (%) 
99950.3%
 
99840.2%
 
99710.1%
 
99630.2%
 
99530.2%
 

Strasse
Categorical

Distinct17
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
A3
559 
A9
466 
A96
155 
A7
130 
A73
129 
Other values (12)
412 
ValueCountFrequency (%) 
A355930.2%
 
A946625.2%
 
A961558.4%
 
A71307.0%
 
A731297.0%
 
A61276.9%
 
A991166.3%
 
A92663.6%
 
A94372.0%
 
A70311.7%
 
Other values (7)351.9%
 
2020-11-13T17:31:49.002386image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)0.1%
2020-11-13T17:31:49.138557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length2
Mean length2.30902215
Min length2

Kat
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
3
881 
7
718 
2
216 
1
 
36
ValueCountFrequency (%) 
388147.6%
 
771838.8%
 
221611.7%
 
1361.9%
 
2020-11-13T17:31:49.270807image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-13T17:31:49.353127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:32:03.206463image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Typ
Real number (ℝ≥0)

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.048082118
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size14.5 KiB
2020-11-13T17:32:03.307681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median6
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.951675744
Coefficient of variation (CV)0.3866172734
Kurtosis0.1886709966
Mean5.048082118
Median Absolute Deviation (MAD)0
Skewness-1.379065019
Sum9344
Variance3.809038212
MonotocityNot monotonic
2020-11-13T17:32:03.411308image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
6129970.2%
 
130016.2%
 
31206.5%
 
71176.3%
 
5110.6%
 
440.2%
 
ValueCountFrequency (%) 
130016.2%
 
31206.5%
 
440.2%
 
5110.6%
 
6129970.2%
 
ValueCountFrequency (%) 
71176.3%
 
6129970.2%
 
5110.6%
 
440.2%
 
31206.5%
 

Betei
Real number (ℝ≥0)

Distinct9
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.276607239
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Memory size14.5 KiB
2020-11-13T17:32:03.511696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum18
Range17
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9626475579
Coefficient of variation (CV)0.422843054
Kurtosis42.7901568
Mean2.276607239
Median Absolute Deviation (MAD)0
Skewness3.802231857
Sum4214
Variance0.9266903208
MonotocityNot monotonic
2020-11-13T17:32:03.605281image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
2113361.2%
 
335519.2%
 
121811.8%
 
41035.6%
 
5251.4%
 
760.3%
 
660.3%
 
840.2%
 
1810.1%
 
ValueCountFrequency (%) 
121811.8%
 
2113361.2%
 
335519.2%
 
41035.6%
 
5251.4%
 
ValueCountFrequency (%) 
1810.1%
 
840.2%
 
760.3%
 
660.3%
 
5251.4%
 

UArt1
Real number (ℝ≥0)

ZEROS

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.388438682
Minimum0
Maximum9
Zeros63
Zeros (%)3.4%
Memory size14.5 KiB
2020-11-13T17:32:03.719934image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile9
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.441722098
Coefficient of variation (CV)0.7206038909
Kurtosis0.3305547855
Mean3.388438682
Median Absolute Deviation (MAD)1
Skewness1.276964923
Sum6272
Variance5.962006804
MonotocityNot monotonic
2020-11-13T17:32:03.817862image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
283144.9%
 
344724.1%
 
81658.9%
 
91246.7%
 
5904.9%
 
1864.6%
 
0633.4%
 
7351.9%
 
660.3%
 
440.2%
 
ValueCountFrequency (%) 
0633.4%
 
1864.6%
 
283144.9%
 
344724.1%
 
440.2%
 
ValueCountFrequency (%) 
91246.7%
 
81658.9%
 
7351.9%
 
660.3%
 
5904.9%
 

UArt2
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)3.4%
Missing1584
Missing (%)85.6%
Infinite0
Infinite (%)0.0%
Mean7.235955056
Minimum0
Maximum9
Zeros4
Zeros (%)0.2%
Memory size14.5 KiB
2020-11-13T17:32:03.922077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q18
median8
Q39
95-th percentile9
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.645847102
Coefficient of variation (CV)0.3656527827
Kurtosis0.1435603787
Mean7.235955056
Median Absolute Deviation (MAD)1
Skewness-1.327325905
Sum1932
Variance7.000506885
MonotocityNot monotonic
2020-11-13T17:32:04.019664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
91337.2%
 
8693.7%
 
3382.1%
 
2110.6%
 
150.3%
 
040.2%
 
740.2%
 
520.1%
 
410.1%
 
(Missing)158485.6%
 
ValueCountFrequency (%) 
040.2%
 
150.3%
 
2110.6%
 
3382.1%
 
410.1%
 
ValueCountFrequency (%) 
91337.2%
 
8693.7%
 
740.2%
 
520.1%
 
410.1%
 

AUrs1
Real number (ℝ≥0)

MISSING

Distinct14
Distinct (%)7.3%
Missing1660
Missing (%)89.7%
Infinite0
Infinite (%)0.0%
Mean76.23560209
Minimum72
Maximum89
Zeros0
Zeros (%)0.0%
Memory size14.5 KiB
2020-11-13T17:32:04.133805image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum72
5-th percentile72
Q173
median73
Q381
95-th percentile89
Maximum89
Range17
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.010691311
Coefficient of variation (CV)0.07884362615
Kurtosis-0.05234210446
Mean76.23560209
Median Absolute Deviation (MAD)1
Skewness1.279196596
Sum14561
Variance36.12841003
MonotocityNot monotonic
2020-11-13T17:32:04.240590image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%) 
73955.1%
 
72412.2%
 
89181.0%
 
82130.7%
 
8880.4%
 
8140.2%
 
8630.2%
 
7520.1%
 
8320.1%
 
8710.1%
 
Other values (4)40.2%
 
(Missing)166089.7%
 
ValueCountFrequency (%) 
72412.2%
 
73955.1%
 
7520.1%
 
7610.1%
 
7710.1%
 
ValueCountFrequency (%) 
89181.0%
 
8880.4%
 
8710.1%
 
8630.2%
 
8410.1%
 

AUrs2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)54.5%
Missing1840
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean78.54545455
Minimum73
Maximum89
Zeros0
Zeros (%)0.0%
Memory size14.5 KiB
2020-11-13T17:32:04.353558image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum73
5-th percentile73
Q174
median80
Q381
95-th percentile86.5
Maximum89
Range16
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.222329679
Coefficient of variation (CV)0.06648799359
Kurtosis-0.2067511111
Mean78.54545455
Median Absolute Deviation (MAD)5
Skewness0.6349656579
Sum864
Variance27.27272727
MonotocityNot monotonic
2020-11-13T17:32:04.444875image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
7330.2%
 
8120.1%
 
7520.1%
 
8020.1%
 
8910.1%
 
8410.1%
 
(Missing)184099.4%
 
ValueCountFrequency (%) 
7330.2%
 
7520.1%
 
8020.1%
 
8120.1%
 
8410.1%
 
ValueCountFrequency (%) 
8910.1%
 
8410.1%
 
8120.1%
 
8020.1%
 
7520.1%
 

AufHi
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)1.8%
Missing1402
Missing (%)75.7%
Infinite0
Infinite (%)0.0%
Mean3.20935412
Minimum0
Maximum9
Zeros2
Zeros (%)0.1%
Memory size14.5 KiB
2020-11-13T17:32:04.554395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q13
median3
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7593475711
Coefficient of variation (CV)0.2366044826
Kurtosis25.89381615
Mean3.20935412
Median Absolute Deviation (MAD)0
Skewness3.838759354
Sum1441
Variance0.5766087337
MonotocityNot monotonic
2020-11-13T17:32:04.648273image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
338020.5%
 
4442.4%
 
5160.9%
 
830.2%
 
020.1%
 
920.1%
 
210.1%
 
110.1%
 
(Missing)140275.7%
 
ValueCountFrequency (%) 
020.1%
 
110.1%
 
210.1%
 
338020.5%
 
4442.4%
 
ValueCountFrequency (%) 
920.1%
 
830.2%
 
5160.9%
 
4442.4%
 
338020.5%
 

Alkoh
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
0
1826 
1
 
25
ValueCountFrequency (%) 
0182698.6%
 
1251.4%
 
2020-11-13T17:32:04.723157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Char1
Categorical

MISSING

Distinct4
Distinct (%)2.5%
Missing1694
Missing (%)91.5%
Memory size14.5 KiB
5
60 
4
56 
6
33 
2
ValueCountFrequency (%) 
5603.2%
 
4563.0%
 
6331.8%
 
280.4%
 
(Missing)169491.5%
 
2020-11-13T17:32:07.496999image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-13T17:32:07.582994image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:32:07.700386image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Char2
Categorical

MISSING

Distinct1
Distinct (%)2.4%
Missing1809
Missing (%)97.7%
Memory size14.5 KiB
6
42 
ValueCountFrequency (%) 
6422.3%
 
(Missing)180997.7%
 
2020-11-13T17:32:07.958931image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-13T17:32:08.039298image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:32:08.120871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Lich1
Categorical

Distinct3
Distinct (%)0.2%
Missing3
Missing (%)0.2%
Memory size14.5 KiB
0
1489 
2
262 
1
 
97
ValueCountFrequency (%) 
0148980.4%
 
226214.2%
 
1975.2%
 
(Missing)30.2%
 
2020-11-13T17:32:08.235696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-13T17:32:08.315078image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:32:11.037586image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Lich2
Categorical

MISSING

Distinct2
Distinct (%)0.6%
Missing1492
Missing (%)80.6%
Memory size14.5 KiB
4
343 
3
 
16
ValueCountFrequency (%) 
434318.5%
 
3160.9%
 
(Missing)149280.6%
 
2020-11-13T17:32:11.159662image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-13T17:32:11.241123image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:32:16.914170image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Zust1
Categorical

Distinct3
Distinct (%)0.2%
Missing5
Missing (%)0.3%
Memory size14.5 KiB
0
1393 
1
413 
2
 
40
ValueCountFrequency (%) 
0139375.3%
 
141322.3%
 
2402.2%
 
(Missing)50.3%
 
2020-11-13T17:32:17.039717image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-13T17:32:17.131937image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:32:28.618748image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Zust2
Categorical

MISSING

Distinct1
Distinct (%)5.9%
Missing1834
Missing (%)99.1%
Memory size14.5 KiB
2
17 
ValueCountFrequency (%) 
2170.9%
 
(Missing)183499.1%
 
2020-11-13T17:32:28.751764image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-13T17:32:28.834997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:32:28.908976image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Fstf
Categorical

MISSING

Distinct7
Distinct (%)0.4%
Missing109
Missing (%)5.9%
Memory size14.5 KiB
2
804 
1
580 
3
290 
4
 
38
S
 
22
Other values (2)
 
8
ValueCountFrequency (%) 
280443.4%
 
158031.3%
 
329015.7%
 
4382.1%
 
S221.2%
 
550.3%
 
F30.2%
 
(Missing)1095.9%
 
2020-11-13T17:32:29.035703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-13T17:32:29.139822image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:32:40.219872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.117774176
Min length1

WoTag
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size14.6 KiB

FeiTag
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
0
1787 
1
 
47
-1
 
17
ValueCountFrequency (%) 
0178796.5%
 
1472.5%
 
-1170.9%
 
2020-11-13T17:32:40.361596image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-13T17:32:40.448362image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:32:46.305244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length1
Mean length1.009184225
Min length1

Month
Categorical

Distinct12
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Jul
238 
Aug
220 
Oct
166 
Sep
162 
Jun
158 
Other values (7)
907 
ValueCountFrequency (%) 
Jul23812.9%
 
Aug22011.9%
 
Oct1669.0%
 
Sep1628.8%
 
Jun1588.5%
 
Apr1508.1%
 
Mar1427.7%
 
Nov1417.6%
 
Dec1377.4%
 
May1377.4%
 
Other values (2)20010.8%
 
2020-11-13T17:32:46.447113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-13T17:32:46.588666image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Interactions

2020-11-13T17:30:28.073814image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:29.389157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:30.725747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:32.029466image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:33.329012image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:34.631672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:35.905791image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:37.227365image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:38.557673image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:39.935268image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:41.253641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:42.553458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:43.798710image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:45.074781image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:46.331170image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:47.559904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:48.829577image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:50.986103image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:51.135248image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:51.252147image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:51.370408image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:51.479838image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:51.605648image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:51.721548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:52.962812image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:53.066803image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:53.186660image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:53.291594image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:53.398378image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:53.506237image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:53.617380image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:53.722362image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:53.829817image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:53.932577image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:55.328929image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:55.349517image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:55.460113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:55.571737image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:55.668682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:55.773890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:55.887583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:55.983765image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:56.087771image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:56.203401image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:56.305269image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:56.412797image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:56.522181image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:56.636820image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:56.744505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:56.993399image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:57.104501image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:58.510890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:58.529189image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:58.628131image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:58.727805image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:58.819452image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:58.924205image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:59.029753image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:59.137940image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:59.236286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:59.339312image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:59.433464image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:59.528548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:59.629064image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:59.726193image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:59.826716image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:30:59.921534image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:00.023203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:01.420454image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:01.438695image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:01.544037image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:01.653948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:01.754298image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:01.862219image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:01.982412image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:02.081145image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:02.193037image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:02.302980image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:02.403482image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:02.501982image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:02.627693image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:02.879121image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:02.986066image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:03.094918image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:03.202390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:04.628566image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:04.648505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:04.754965image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:04.870413image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:04.979245image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:05.085671image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:05.201003image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:05.301083image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:05.400665image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:05.513238image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:05.618694image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:05.721568image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:05.837847image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:05.946760image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:06.048468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:06.161780image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:06.266982image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:07.603822image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:07.623125image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:07.719244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:07.819409image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:07.915290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:08.023526image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:08.126635image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:08.217928image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:08.304268image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:08.405381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:08.510386image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:08.743900image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:08.846416image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:08.950362image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:09.045446image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:09.155435image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:09.258627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:10.647180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:10.665545image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:10.759575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:10.857764image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:10.954162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:11.052337image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:11.146895image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:11.240326image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:11.334498image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:11.439253image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:11.533093image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:11.618994image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:11.716270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:11.807098image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:11.902531image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:11.994967image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:12.086737image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:13.507288image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:13.526894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:13.638551image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:13.760662image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:13.869132image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:13.985624image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:14.111821image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:14.225194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:14.324397image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:14.575984image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:14.684057image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:14.789185image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:14.900111image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:15.009055image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:15.115462image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:15.224969image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:15.339132image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:16.732709image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:16.755049image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:16.865970image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:16.980496image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:17.079463image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:17.198469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:17.305981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:17.409098image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:17.508045image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:17.631155image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:17.730609image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:17.828909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:17.933035image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:18.039306image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:18.144015image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:18.244923image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:18.347337image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:19.853734image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:19.872894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:19.973186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:20.078268image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:20.196541image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:20.301814image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:20.404278image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:20.647117image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:20.749729image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:20.855938image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:20.951615image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:21.052660image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:21.162199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:21.277931image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:21.395537image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:21.504202image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:21.614919image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:23.204518image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:23.225353image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:23.333379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:23.438539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:23.538955image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:23.644215image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:23.746049image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:23.846751image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:23.940388image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:24.050452image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:24.165550image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:24.265735image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:24.371574image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:24.477626image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:24.580883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:24.682977image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:24.781216image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:26.140110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:26.159634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:26.271639image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:26.384353image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:26.497185image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:26.747675image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:26.868859image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:26.966674image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:27.065155image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:27.180020image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:27.278483image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:27.382245image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:27.491555image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:27.607694image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:27.716109image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:27.828283image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:27.936059image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:29.306357image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:29.325079image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:29.420004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:29.522279image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:29.617757image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:29.716440image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:29.820606image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:29.915663image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:30.003557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:30.111180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:30.213346image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:30.305095image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:30.406466image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:30.503872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:30.603134image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:30.699605image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:30.790631image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:32.107816image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:32.128539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:32.231790image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:32.473211image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:32.578052image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:32.676920image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:32.780410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:32.879615image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:32.968920image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:33.074351image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:33.169108image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:33.262505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:33.361270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:33.458669image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:33.552693image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:33.651956image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:33.747021image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:35.180446image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:35.201592image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:35.327933image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:35.444835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:35.548794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:35.677521image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:35.792657image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:35.898475image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:36.000520image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:36.122865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:36.231696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:36.332953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:36.449473image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:36.564467image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:36.671353image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:36.771113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:36.874993image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:38.355218image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:38.520950image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:38.637922image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:38.750489image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:38.861956image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:38.984577image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:39.100620image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:39.212905image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:39.322515image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:39.435134image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:39.535215image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:39.637713image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:39.740337image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:39.851579image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:39.959007image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:40.062420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:40.170478image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-11-13T17:32:48.000126image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-11-13T17:32:49.344511image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-11-13T17:32:50.662444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-11-13T17:32:51.946566image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-11-13T17:32:52.150640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-11-13T17:31:41.999372image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:43.612226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:43.787341image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-13T17:31:45.339527image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

df_indexTempMaxTempAvgSpatMaxSpatAvgTempDistSpatDistCoverageTLCarTLHGVStrasseKatTypBeteiUArt1UArt2AUrs1AUrs2AufHiAlkohChar1Char2Lich1Lich2Zust1Zust2FstfWoTagFeiTagMonth
003602226568431100611714718A32132NaNNaNNaNNaN0NaNNaN0.0NaN1.0NaN2Di1Jan
11692860003475100411691686A63632NaN89.0NaNNaN0NaNNaN0.0NaN0.0NaN2Di1Jan
221628913925721200501293804A336529.0NaNNaN3.00NaNNaN0.0NaN1.0NaN2Mi0Jan
33162891392572121996501293804A33672NaN82.0NaNNaN0NaNNaN0.0NaN1.0NaN2Mi0Jan
441624920701584700281417502A33622NaNNaNNaNNaN0NaNNaN0.0NaN0.0NaNNaNMi0Jan
5545207483305700421044780A63632NaNNaNNaNNaN1NaNNaN0.0NaN0.0NaN1Mi0Jan
6628511718067506800281205643A97133NaN72.0NaNNaN0NaNNaN0.0NaN1.02.01Mi-1Jan
7721696129915615110431647670A33733NaNNaNNaNNaN0NaNNaN2.04.01.0NaN2Do0Jan
88138556415314200421803985A97123NaNNaNNaNNaN0NaNNaN2.04.00.0NaN1Fr0Jan
9910561994125550112221657905A93632NaNNaNNaNNaN0NaNNaN2.04.01.0NaN4Fr0Jan

Last rows

df_indexTempMaxTempAvgSpatMaxSpatAvgTempDistSpatDistCoverageTLCarTLHGVStrasseKatTypBeteiUArt1UArt2AUrs1AUrs2AufHiAlkohChar1Char2Lich1Lich2Zust1Zust2FstfWoTagFeiTagMonth
1841185781612698236080861305511A73119NaNNaNNaN3.006.0NaN2.04.00.0NaN2Fr0Dec
184218582375229229630500211269784A93632NaNNaNNaNNaN0NaNNaN0.0NaN0.0NaNFFr0Dec
184318595649443244704700161785638A731429.0NaNNaN3.00NaNNaN0.0NaN0.0NaN2-10Dec
1844186020193149994372160291875579A73622NaNNaNNaNNaN0NaNNaN0.0NaN0.0NaN1Sa0Dec
18451861452639552768220751262925A93622NaNNaNNaNNaN0NaNNaN0.0NaN0.0NaN1So0Dec
1846186239311345610007110741850582A93734NaNNaNNaNNaN0NaNNaN2.04.00.0NaN3So0Dec
18471863135546481278412750421798511A97622NaNNaNNaNNaN0NaNNaN0.0NaN0.0NaN1So0Dec
1848186487793788341100881363741A923622NaNNaNNaNNaN1NaNNaN2.04.00.0NaN2So0Dec
1849186593723418257140751950993A33632NaNNaNNaNNaN0NaNNaN2.03.00.0NaN2-10Dec
1850186669621406126060781155500A712622NaNNaNNaNNaN0NaNNaN0.0NaN0.0NaN1Di0Dec